Spectral Fault Receptive Fields (SFRFs) are a biologically inspired computational framework for analyzing vibration and spectral signals. They act as optimized contrast filters that emphasize characteristic fault frequencies, making degradation patterns more detectable and interpretable. This toolbox implements the complete SFRF workflow, including: Bearing geometry modelling Automatic computation of characteristic fault-frequency bands Center–surround receptive-field gain functions SFRF computation from temporal or spectral data Parallel-ready FFT and SFRF ensemble processors SFRFs strengthen the link between spectral patterns and machine condition, enabling early fault detection and diagnosis-informed prognosis for rotating machinery. About this Release This record archives the exact source code snapshot and MATLAB toolbox package corresponding to the official v1.0.0 GitHub release of the SFRFs Toolbox. It includes: the packaged toolbox: SFRFsToolbox_v1.0.0.mltbx the complete source code: matlab-sfrfs-v1.0.0.zip diagrams, documentation, and development notes(in the devel and doc folders inside the source archive) Full documentation and API reference are available in the GitHub project. Funding This work was carried out within the framework of the ARCHIMEDES project, supported by the Chips Joint Undertaking under Grant Agreement No. 101112295, with co-funding from National Authorities. Additional support was provided by the Austrian Research Promotion Agency (FFG) under Grant Agreement No. FO999899377.